توضیحاتی در مورد کتاب Collaborative Logistics and Intermodality: Integration in Supply Chain Network Models and Solutions for Global Environments
نام کتاب : Collaborative Logistics and Intermodality: Integration in Supply Chain Network Models and Solutions for Global Environments
عنوان ترجمه شده به فارسی : لجستیک مشارکتی و ترکیبی: یکپارچه سازی در مدل های شبکه زنجیره تامین و راه حل ها برای محیط های جهانی
سری :
نویسندگان : Jorge E. Hernández (editor), Dong Li (editor), José Elias Jimenez-Sanchez (editor), Miguel Gaston Cedillo-Campos (editor), Luo Wenping (editor)
ناشر : Springer
سال نشر : 2021
تعداد صفحات : 184
ISBN (شابک) : 3030509567 , 9783030509569
زبان کتاب : English
فرمت کتاب : pdf
حجم کتاب : 4 مگابایت
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فهرست مطالب :
Preface
References
Contents
Challenges and Developments in Integrated Container Supply Chains: A Research Agenda for the Europe-China Research Network on ...
1 Introduction
2 CSC Integration and Performance
3 Safety Analysis of CSCs
4 Security Management of CSCs
5 Sustainable CSC Management
6 Information and Communication Technology (ICT)
7 Intermodal Management in CSCs
8 Conclusion
References
A Research Framework for Cross-National Comparative Logistics
1 Introduction
2 Define the Field and Research Problems
3 What to Compare in Cross-National Comparative Logistics
4 Dimension of Logistics to Compare
4.1 Logistics Concepts and Thoughts
4.2 Logistics Practices
4.3 Sub-areas of Logistics to Compare
5 Conceptualizing the Models
5.1 Development Level Model
5.2 Economic System Model
5.3 Cultural Model
6 Conclusion
References
Supply Chain Solutions to Upstream Buyer Consolidation with Green and Resilient Supply Chain Designs in the China-Europe Conta...
1 Introduction
2 Literature Review
2.1 Asia-Europe Sea Container Supply Chain Configurations
2.2 The Potential of Shortsea/Rail Based Intermodal Transport
2.3 Risk and Resilient Supply Chains
2.4 Logistics Industry in China Under the Context of International Trade
3 Methodology
4 Presenting Data
4.1 Concept BAU: Consolidation in Customer Country (Fig. 3a)
4.2 Concept A1: Upstream Consolidation for One Buyer (Fig. 3b)
4.3 Concept A2: Upstream Consolidation for a Group of Buyers (Fig. 3c)
4.4 Concept B: Upstream and Downstream Buyer Consolidation (Fig. 3d)
4.5 Concept C: Upstream and Downstream Buyer Consolidation with Intermodal Transport Solution in Europe (Fig. 3e)
5 Discussion
5.1 Strengths and Weaknesses of the Identified Supply Chain Designs
5.2 Who Are the Decision-Makers?
5.3 Impediments to Upstream Buyer Consolidation
6 Practices to a Resilient Supply Chain
6.1 Risks in the Supply Chain
6.2 Potential Risk-Mitigating Strategies
7 Concluding Remarks and Implications
7.1 Conclusions
7.2 Limitations and Scope for Further Research
References
Impact Analysis of Slow Steaming on Inland River Container Freight Supply Chain
1 Problem Description
1.1 Basic Problem Description
1.2 Model Symbol
1.3 Model Hypothesis
1.4 Model Definition
2 Model Construction of Container Freight Supply Chain Control System
2.1 Consignee Model
2.2 Shipper Model
3 Model Validation
3.1 Transportation Time at Five Speeds
3.2 The Optimal Solution and Suggestion of Consignee Inventory Model
3.3 The Optimal Solution and Suggestion of the Shipper Inventory Model
4 Conclusion
References
Modelling Container Port Logistics and Intermodality from the Perspective of Environmental Sustainability
1 Introduction
2 Related Literature
3 Modeling Approach
4 Background Information About the Case Study
4.1 Container Port and Its Hinterland
4.1.1 Port of Shanghai
4.1.2 Yangtze River Economic Belt
4.2 Port Logistics and Intermodality
4.2.1 Roadway
4.2.2 Railway
4.2.3 Waterway
5 Numerical Analysis
5.1 Assumptions About the Parameters of the Model
5.2 Equilibrium Results
6 Conclusions and Policy Implications
References
Random Forest Regression Model Application for Prediction of China´s Railway Freight Volume
1 Introduction
2 Literature Review
3 Random Forest Regression Prediction of Chinese Railway Freight Volume
3.1 Random Forest Regression Introduction
3.2 Random Forest Regression Testing
3.3 Feature Variable Selection
3.4 Data Collecting and Checking
3.5 Model and Solution
3.6 Evaluation of Random Forest Regression and Linear Regression
3.7 Chinese Freight Volume Prediction for 2017
3.8 Comparison of the Two Models
4 Conclusions
Appendix Table. Chinese Railway Freight and Other Industry Data
References
An Optimization Approach for the Train Load Planning Problem in Seaport Container Terminals
1 Introduction
2 Problem Definition and Mathematical Formulation
2.1 A Simple Initialization Heuristics
3 The MIP Heuristic Solution Approach
4 Experimental Analysis
5 Conclusions
References
Utilizing Breakthrough Innovations: The Need for Information Sharing as a New Key Performance Indicator for Container Port Ope...
1 Introduction
2 Related Literature
2.1 Input and Output Selection Using Data Envelopment Analysis
2.2 The Smart Port Project
2.3 Woo, Pettit and Beresford (2011)
2.4 Incremental Versus Breakthrough Innovations
3 Case Study: Performance of Oslo Port
3.1 Oslo Port
3.2 Performance Measurement by Oslo Port Authority
3.2.1 Container Throughput
3.2.2 Area Efficiency
3.2.3 Crane Efficiency
3.2.4 Gate-to-Gate Time
3.3 Potential to Improve the Overall Performance
3.3.1 Traffic Congestion
3.3.2 Container Sequence
3.3.3 Discussion
3.3.4 Further Evidence of the Importance of Information Sharing
The Port-Ship Coordinated Planning (PoShCoP) Project
Workload Variance
3.3.5 Relations Between Supply Chain Actors and Information Sharing
4 Information Sharing as a New Performance Indicator
4.1 Example of Usage in Oslo Port
4.2 Including the Information Sharing Indicator in the Performance Measurement Framework
5 Conclusion
References
Scheduling Periodical Deliveries from a Distribution Centre to Minimize the Fleet Size
1 Introduction
2 Problem with the Same Delivery Frequency for All Customers
2.1 A Routing-then-Scheduling Approach
2.2 An Algorithm for Route Scheduling
2.3 Properties of the Solution
2.4 Alternative Schedules with the Same Fleet Size
3 Problem with Different Delivery Frequencies
3.1 A General Integer Programming Model
3.2 A Two-Stage Method
3.3 An Extended Routing-then-Scheduling Approach
4 Computational Experiments
4.1 Testing the Route Assignment Models
4.2 Test on Benchmark Examples
5 Conclusions
References